fix typos (#639)

egs/csj/ASR/.gitignore

@@ -1,7 +1,8 @@
-librispeech_*.*
+librispeech_*
 todelete*
 lang*
 notify_tg.py
 finetune_*
 misc.ini
-.vscode/*
+.vscode/*
+offline/*

egs/csj/ASR/local/compute_fbank_musan.py

@@ -1 +0,0 @@
-../../../librispeech/ASR/local/compute_fbank_musan.py

egs/csj/ASR/local/compute_fbank_musan.py

@@ -0,0 +1,127 @@
+#!/usr/bin/env python3
+# Copyright    2021  Xiaomi Corp.        (authors: Fangjun Kuang)
+#
+# See ../../../../LICENSE for clarification regarding multiple authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+import logging
+import os
+from pathlib import Path
+
+import torch
+from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter, combine
+from lhotse.recipes.utils import read_manifests_if_cached
+
+from icefall.utils import get_executor
+
+
+ARGPARSE_DESCRIPTION = """
+This file computes fbank features of the musan dataset.
+It looks for manifests in the directory data/manifests.
+
+The generated fbank features are saved in data/fbank.
+"""
+
+# Torch's multithreaded behavior needs to be disabled or
+# it wastes a lot of CPU and slow things down.
+# Do this outside of main() in case it needs to take effect
+# even when we are not invoking the main (e.g. when spawning subprocesses).
+torch.set_num_threads(1)
+torch.set_num_interop_threads(1)
+
+
+def compute_fbank_musan(manifest_dir: Path, fbank_dir: Path):
+    # src_dir = Path("data/manifests")
+    # output_dir = Path("data/fbank")
+    num_jobs = min(15, os.cpu_count())
+    num_mel_bins = 80
+
+    dataset_parts = (
+        "music",
+        "speech",
+        "noise",
+    )
+    prefix = "musan"
+    suffix = "jsonl.gz"
+    manifests = read_manifests_if_cached(
+        dataset_parts=dataset_parts,
+        output_dir=manifest_dir,
+        prefix=prefix,
+        suffix=suffix,
+    )
+    assert manifests is not None
+
+    assert len(manifests) == len(dataset_parts), (
+        len(manifests),
+        len(dataset_parts),
+        list(manifests.keys()),
+        dataset_parts,
+    )
+
+    musan_cuts_path = fbank_dir / "musan_cuts.jsonl.gz"
+
+    if musan_cuts_path.is_file():
+        logging.info(f"{musan_cuts_path} already exists - skipping")
+        return
+
+    logging.info("Extracting features for Musan")
+
+    extractor = Fbank(FbankConfig(num_mel_bins=num_mel_bins))
+
+    with get_executor() as ex:  # Initialize the executor only once.
+        # create chunks of Musan with duration 5 - 10 seconds
+        musan_cuts = (
+            CutSet.from_manifests(
+                recordings=combine(
+                    part["recordings"] for part in manifests.values()
+                )
+            )
+            .cut_into_windows(10.0)
+            .filter(lambda c: c.duration > 5)
+            .compute_and_store_features(
+                extractor=extractor,
+                storage_path=f"{fbank_dir}/musan_feats",
+                num_jobs=num_jobs if ex is None else 80,
+                executor=ex,
+                storage_type=LilcomChunkyWriter,
+            )
+        )
+        musan_cuts.to_file(musan_cuts_path)
+
+
+def get_args():
+    parser = argparse.ArgumentParser(
+        description=ARGPARSE_DESCRIPTION,
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+    )
+
+    parser.add_argument(
+        "--manifest-dir", type=Path, help="Path to save manifests"
+    )
+    parser.add_argument(
+        "--fbank-dir", type=Path, help="Path to save fbank features"
+    )
+
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = get_args()
+    formatter = (
+        "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
+    )
+
+    logging.basicConfig(format=formatter, level=logging.INFO)
+    compute_fbank_musan(args.manifest_dir, args.fbank_dir)

egs/csj/ASR/prepare.sh

@@ -2,7 +2,7 @@
 # We assume the following directories are downloaded.
 #
 #  - $csj_dir
-#     CSJ is assumed to be the USB-type directory, which should contain the following subdirectories:- 
+#     CSJ is assumed to be the USB-type directory, which should contain the following subdirectories:-
 #     - DATA (not used in this script)
 #     - DOC (not used in this script)
 #     - MODEL (not used in this script)
@@ -30,7 +30,7 @@
 #     - music
 #     - noise
 #     - speech
-# 
+#
 # By default, this script produces the original transcript like kaldi and espnet. Optionally, you
 # can generate other transcript formats by supplying your own config files. A few examples of these
 # config files can be found in local/conf.
@@ -58,15 +58,15 @@ log() {
     echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
 }
 
-if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then 
+if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
     log "Stage 1: Prepare CSJ manifest"
     # If you want to generate more transcript modes, append the path to those config files at c.
     # Example: lhotse prepare csj $csj_dir $trans_dir $csj_manifest_dir -c local/conf/disfluent.ini
     # NOTE: In case multiple config files are supplied, the second config file and onwards will inherit
-    #       the segment boundaries of the first config file. 
-    if [ ! -e $csj_manifest_dir/.librispeech.done ]; then 
+    #       the segment boundaries of the first config file.
+    if [ ! -e $csj_manifest_dir/.csj.done ]; then
         lhotse prepare csj $csj_dir $trans_dir $csj_manifest_dir -j 4
-        touch $csj_manifest_dir/.librispeech.done
+        touch $csj_manifest_dir/.csj.done
     fi
 fi
 
@@ -85,20 +85,20 @@ if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
         python local/compute_fbank_csj.py --manifest-dir $csj_manifest_dir \
             --fbank-dir $csj_fbank_dir
         parts=(
-            train 
+            train
             valid
             eval1
             eval2
             eval3
         )
-        for part in ${parts[@]}; do 
+        for part in ${parts[@]}; do
             python local/validate_manifest.py --manifest $csj_manifest_dir/csj_cuts_$part.jsonl.gz
         done
         touch $csj_fbank_dir/.csj-validated.done
     fi
 fi
 
-if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then 
+if [ $stage -le 4 ] && [ $stop_stage -ge 4 ]; then
     log "Stage 4: Prepare CSJ lang"
     modes=disfluent
 
@@ -117,14 +117,14 @@ if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
   log "Stage 5: Compute fbank for musan"
     mkdir -p $musan_fbank_dir
 
-    if [ ! -e $musan_fbank_dir/.musan.done ]; then 
+    if [ ! -e $musan_fbank_dir/.musan.done ]; then
         python local/compute_fbank_musan.py --manifest-dir $musan_manifest_dir --fbank-dir $musan_fbank_dir
         touch $musan_fbank_dir/.musan.done
     fi
 fi
 
-if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then 
+if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
     log "Stage 6: Show manifest statistics"
     python local/display_manifest_statistics.py --manifest-dir $csj_manifest_dir > $csj_manifest_dir/manifest_statistics.txt
     cat $csj_manifest_dir/manifest_statistics.txt
-fi
+fi